If the idea of cohorts in marketing feels familiar, it is. It’s been around for a long time — I even explained cohort analysis in Google Analytics back in 2015. The application for cohort analysis has grown among marketers, and Google had to keep up, particularly with the recent redesign of Google Analytics, GA4. Enter the updated cohort analysis in GA4.
A cohort is a group of people, things, or events that share statistical factor — like age, class, and time periods. In marketing cohorts are meant to identify a demographic.
One of the reasons cohorts is vital to advanced marketing is because of the capability to sort the type of traffic arriving to your website and to sort through the type of traffic that is created from your content and digital marketing ads. Reviewing general visitor metrics like returning visitors can provide a general overview of traffic type.
But an aggregate view conceals segments that may be consistently converting, and thus are worth further engagement. The statistical means in cohort analysis yields a clearer signal of a trend.
A good cohort can help a marketing team identify which portion of a customers is responding to campaign tactics. You can look at an aggregate of visits and tell if there’s a particular portion of aggregate visits representing people responding to a white paper download or watching a video.
Thus cohorts are useful for applying campaign budgets to the activity that will likely yield more results.
Accessing Cohorts Analysis in GA4
The cohort analysis in Google Analytics was originally a stand alone beta report created from four parameters — cohort type, size, metrics, and date range. Within GA4, analysts have gained more flexibility in how the data is selected. This leads to more presentation options to fit the analyst’s needs.
To access the cohort, you select “Analysis” in the main menu of your Google Analytics profile. You would next select “Cohorts, which takes you to the analytics hub. Analytics hub is a new feature in GA4 that consolidates many of the stand alone reports into selection menus. The selection menu displays the choices for dimensions, metrics, and associated features
Once in the hub, analysts can enter two condition settings that act as “bookends” for setting the cohort type. Configuration establishes the condition in which visits to a website or app are included in a cohort. A second setting, return, establishes a second criteria in which visits to a website or app are considered part of a cohort. Both settings include selections for first touch (the date in which a customers arrives on a site or app), any transaction on the site or app, and any conversion from that transaction.
The cohort size is controlled with cohort granularity. The user can define the initial and returned cohort period of time by day, week, or month. There is also a breakdown feature that further divides subgroups based on a selected dimension. Values determine the metrics to be displayed.
Related Article: What Marketers Need to Know About Google Analytics 4
Google Adds 3 New Cohort Calculation Capabilities
Three new cohost calculations join the standard cohort module of Google Analytics 4.
Standard calculation lets you identify the cohort users that return in each specific period. Standard calculation is similar to the cohort report I mentioned in the previous Google Analytics version. It displays a standard cohort chart with weeks along the top horizontal axis and aggregate users by cohort dates along the vertical axis.
Then there is rolling calculation. A rolling calculation lets you identify users that return in every period after being included in the cohort.
Google offers an example. The standard calculation for the example image indicates 35 users were acquired on Nov. 23 and they also returned to your site 3 days later. If you switch to a rolling calculation, you would see a different number, 6, indicating these users came back every day from Nov. 23 to 3 days later. In other words, they had exposure to your site on a rolling basis.
The second new selection, cumulative calculation, allows you to cumulate the selected metric for users who have returned in any period after being included in the cohort. So using our example, this setting displays a sum for a metric like spend for those users who came back over those 3 days.
Finally there is a per cohort size metric calculation. It displays the results relative to the size of each cohort, permitting easy behavior comparison of cohorts of different sizes.
Once everything is selected, analysts can monitor how user behavior changes over time by examining the cohorts with varying dates according to campaign influences.
Understanding the Limitations of Cohort Analysis
There are limits in the cohort analysis, however. Google Analytics can show a maximum of 60 cohorts, which should be sufficient for many digital campaigns, but the limit can be a hindrance if your cohort inputs are complex. In addition, when applying a breakdown dimension to a cohort, only the top 15 values of that dimension are shown.
Cohorts isolate data to guide you to where the greatest impact of marketing is occurring. The new cohort analysis features in Google Analytics 4 provide more nuanced guidance to the activity customers find valuable on your website or in your app.